
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 20 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* phi1 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (cos (* 0.5 phi2)))
(t_3 (* (cos phi1) (cos phi2)))
(t_4 (sin (* phi1 0.5))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_3 (* t_1 t_1))
(pow (- (* t_2 t_4) (* t_0 (sin (* 0.5 phi2)))) 2.0)))
(sqrt
(+
(- 1.0 (pow (fma t_2 t_4 (* t_0 (sin (* phi2 -0.5)))) 2.0))
(*
t_3
(-
(/
(+ (* (cos lambda1) (cos lambda2)) (* (sin lambda1) (sin lambda2)))
2.0)
0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos((0.5 * phi2));
double t_3 = cos(phi1) * cos(phi2);
double t_4 = sin((phi1 * 0.5));
return R * (2.0 * atan2(sqrt(((t_3 * (t_1 * t_1)) + pow(((t_2 * t_4) - (t_0 * sin((0.5 * phi2)))), 2.0))), sqrt(((1.0 - pow(fma(t_2, t_4, (t_0 * sin((phi2 * -0.5)))), 2.0)) + (t_3 * ((((cos(lambda1) * cos(lambda2)) + (sin(lambda1) * sin(lambda2))) / 2.0) - 0.5))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = cos(Float64(0.5 * phi2)) t_3 = Float64(cos(phi1) * cos(phi2)) t_4 = sin(Float64(phi1 * 0.5)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_3 * Float64(t_1 * t_1)) + (Float64(Float64(t_2 * t_4) - Float64(t_0 * sin(Float64(0.5 * phi2)))) ^ 2.0))), sqrt(Float64(Float64(1.0 - (fma(t_2, t_4, Float64(t_0 * sin(Float64(phi2 * -0.5)))) ^ 2.0)) + Float64(t_3 * Float64(Float64(Float64(Float64(cos(lambda1) * cos(lambda2)) + Float64(sin(lambda1) * sin(lambda2))) / 2.0) - 0.5))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$3 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(t$95$2 * t$95$4), $MachinePrecision] - N[(t$95$0 * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(t$95$2 * t$95$4 + N[(t$95$0 * N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$3 * N[(N[(N[(N[(N[Cos[lambda1], $MachinePrecision] * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision] + N[(N[Sin[lambda1], $MachinePrecision] * N[Sin[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \left(0.5 \cdot \phi_2\right)\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
t_4 := \sin \left(\phi_1 \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 \cdot \left(t\_1 \cdot t\_1\right) + {\left(t\_2 \cdot t\_4 - t\_0 \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}}}{\sqrt{\left(1 - {\left(\mathsf{fma}\left(t\_2, t\_4, t\_0 \cdot \sin \left(\phi_2 \cdot -0.5\right)\right)\right)}^{2}\right) + t\_3 \cdot \left(\frac{\cos \lambda_1 \cdot \cos \lambda_2 + \sin \lambda_1 \cdot \sin \lambda_2}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified62.9%
div-sub62.9%
sin-diff63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr63.8%
div-sub62.9%
sin-diff63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr77.8%
*-commutative77.8%
*-commutative77.8%
fmm-def77.8%
*-commutative77.8%
*-commutative77.8%
*-commutative77.8%
distribute-lft-neg-in77.8%
sin-neg77.8%
distribute-rgt-neg-in77.8%
metadata-eval77.8%
*-commutative77.8%
*-commutative77.8%
Simplified77.8%
sin-mult77.9%
cos-sum77.9%
cos-277.9%
div-sub77.9%
+-inverses77.9%
Applied egg-rr77.9%
cos-077.9%
metadata-eval77.9%
Simplified77.9%
cos-diff78.5%
Applied egg-rr78.5%
Final simplification78.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* phi1 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (cos (* 0.5 phi2)))
(t_3 (* (cos phi1) (cos phi2)))
(t_4 (sin (* phi1 0.5))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_3 (* t_1 t_1))
(pow (- (* t_2 t_4) (* t_0 (sin (* 0.5 phi2)))) 2.0)))
(sqrt
(+
(- 1.0 (cbrt (pow (fma t_4 t_2 (* t_0 (sin (* phi2 -0.5)))) 6.0)))
(* t_3 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos((0.5 * phi2));
double t_3 = cos(phi1) * cos(phi2);
double t_4 = sin((phi1 * 0.5));
return R * (2.0 * atan2(sqrt(((t_3 * (t_1 * t_1)) + pow(((t_2 * t_4) - (t_0 * sin((0.5 * phi2)))), 2.0))), sqrt(((1.0 - cbrt(pow(fma(t_4, t_2, (t_0 * sin((phi2 * -0.5)))), 6.0))) + (t_3 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = cos(Float64(0.5 * phi2)) t_3 = Float64(cos(phi1) * cos(phi2)) t_4 = sin(Float64(phi1 * 0.5)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_3 * Float64(t_1 * t_1)) + (Float64(Float64(t_2 * t_4) - Float64(t_0 * sin(Float64(0.5 * phi2)))) ^ 2.0))), sqrt(Float64(Float64(1.0 - cbrt((fma(t_4, t_2, Float64(t_0 * sin(Float64(phi2 * -0.5)))) ^ 6.0))) + Float64(t_3 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$3 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(t$95$2 * t$95$4), $MachinePrecision] - N[(t$95$0 * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Power[N[(t$95$4 * t$95$2 + N[(t$95$0 * N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 6.0], $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision] + N[(t$95$3 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \left(0.5 \cdot \phi_2\right)\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
t_4 := \sin \left(\phi_1 \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 \cdot \left(t\_1 \cdot t\_1\right) + {\left(t\_2 \cdot t\_4 - t\_0 \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}}}{\sqrt{\left(1 - \sqrt[3]{{\left(\mathsf{fma}\left(t\_4, t\_2, t\_0 \cdot \sin \left(\phi_2 \cdot -0.5\right)\right)\right)}^{6}}\right) + t\_3 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified62.9%
div-sub62.9%
sin-diff63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr63.8%
div-sub62.9%
sin-diff63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr77.8%
*-commutative77.8%
*-commutative77.8%
fmm-def77.8%
*-commutative77.8%
*-commutative77.8%
*-commutative77.8%
distribute-lft-neg-in77.8%
sin-neg77.8%
distribute-rgt-neg-in77.8%
metadata-eval77.8%
*-commutative77.8%
*-commutative77.8%
Simplified77.8%
sin-mult77.9%
cos-sum77.9%
cos-277.9%
div-sub77.9%
+-inverses77.9%
Applied egg-rr77.9%
cos-077.9%
metadata-eval77.9%
Simplified77.9%
add-cbrt-cube77.9%
pow377.9%
pow-pow77.9%
Applied egg-rr77.9%
Final simplification77.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(pow
(fma
(cos (* 0.5 phi2))
(sin (* phi1 0.5))
(* (cos (* phi1 0.5)) (sin (* phi2 -0.5))))
2.0))
(t_2 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_2 (* t_0 t_0)) t_1))
(sqrt
(+ (- 1.0 t_1) (* t_2 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(fma(cos((0.5 * phi2)), sin((phi1 * 0.5)), (cos((phi1 * 0.5)) * sin((phi2 * -0.5)))), 2.0);
double t_2 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0 - t_1) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = fma(cos(Float64(0.5 * phi2)), sin(Float64(phi1 * 0.5)), Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * -0.5)))) ^ 2.0 t_2 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_2 * Float64(t_0 * t_0)) + t_1)), sqrt(Float64(Float64(1.0 - t_1) + Float64(t_2 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] + N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$2 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] + N[(t$95$2 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\left(\mathsf{fma}\left(\cos \left(0.5 \cdot \phi_2\right), \sin \left(\phi_1 \cdot 0.5\right), \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot -0.5\right)\right)\right)}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 \cdot \left(t\_0 \cdot t\_0\right) + t\_1}}{\sqrt{\left(1 - t\_1\right) + t\_2 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified62.9%
div-sub62.9%
sin-diff63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr63.8%
div-sub62.9%
sin-diff63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr77.8%
*-commutative77.8%
*-commutative77.8%
fmm-def77.8%
*-commutative77.8%
*-commutative77.8%
*-commutative77.8%
distribute-lft-neg-in77.8%
sin-neg77.8%
distribute-rgt-neg-in77.8%
metadata-eval77.8%
*-commutative77.8%
*-commutative77.8%
Simplified77.8%
sin-mult77.9%
cos-sum77.9%
cos-277.9%
div-sub77.9%
+-inverses77.9%
Applied egg-rr77.9%
cos-077.9%
metadata-eval77.9%
Simplified77.9%
Taylor expanded in phi1 around inf 77.9%
fmm-def77.9%
distribute-rgt-neg-in77.9%
sin-neg77.9%
distribute-lft-neg-in77.9%
metadata-eval77.9%
*-commutative77.9%
Simplified77.9%
Final simplification77.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* phi1 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (cos (* 0.5 phi2)))
(t_3 (* (cos phi1) (cos phi2)))
(t_4 (sin (* phi1 0.5))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_3 (* t_1 t_1))
(pow (- (* t_2 t_4) (* t_0 (sin (* 0.5 phi2)))) 2.0)))
(sqrt
(+
(- 1.0 (pow (fma t_2 t_4 (* t_0 (sin (* phi2 -0.5)))) 2.0))
(* t_3 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos((0.5 * phi2));
double t_3 = cos(phi1) * cos(phi2);
double t_4 = sin((phi1 * 0.5));
return R * (2.0 * atan2(sqrt(((t_3 * (t_1 * t_1)) + pow(((t_2 * t_4) - (t_0 * sin((0.5 * phi2)))), 2.0))), sqrt(((1.0 - pow(fma(t_2, t_4, (t_0 * sin((phi2 * -0.5)))), 2.0)) + (t_3 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = cos(Float64(0.5 * phi2)) t_3 = Float64(cos(phi1) * cos(phi2)) t_4 = sin(Float64(phi1 * 0.5)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_3 * Float64(t_1 * t_1)) + (Float64(Float64(t_2 * t_4) - Float64(t_0 * sin(Float64(0.5 * phi2)))) ^ 2.0))), sqrt(Float64(Float64(1.0 - (fma(t_2, t_4, Float64(t_0 * sin(Float64(phi2 * -0.5)))) ^ 2.0)) + Float64(t_3 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$3 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(t$95$2 * t$95$4), $MachinePrecision] - N[(t$95$0 * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(t$95$2 * t$95$4 + N[(t$95$0 * N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$3 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \left(0.5 \cdot \phi_2\right)\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
t_4 := \sin \left(\phi_1 \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 \cdot \left(t\_1 \cdot t\_1\right) + {\left(t\_2 \cdot t\_4 - t\_0 \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}}}{\sqrt{\left(1 - {\left(\mathsf{fma}\left(t\_2, t\_4, t\_0 \cdot \sin \left(\phi_2 \cdot -0.5\right)\right)\right)}^{2}\right) + t\_3 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified62.9%
div-sub62.9%
sin-diff63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr63.8%
div-sub62.9%
sin-diff63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr77.8%
*-commutative77.8%
*-commutative77.8%
fmm-def77.8%
*-commutative77.8%
*-commutative77.8%
*-commutative77.8%
distribute-lft-neg-in77.8%
sin-neg77.8%
distribute-rgt-neg-in77.8%
metadata-eval77.8%
*-commutative77.8%
*-commutative77.8%
Simplified77.8%
sin-mult77.9%
cos-sum77.9%
cos-277.9%
div-sub77.9%
+-inverses77.9%
Applied egg-rr77.9%
cos-077.9%
metadata-eval77.9%
Simplified77.9%
Final simplification77.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* phi1 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (cos (* 0.5 phi2)) (sin (* phi1 0.5))))
(t_3 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt
(+ (* t_3 (* t_1 t_1)) (pow (- t_2 (* t_0 (sin (* 0.5 phi2)))) 2.0)))
(sqrt
(+
(- 1.0 (pow (+ (* t_0 (sin (* phi2 -0.5))) t_2) 2.0))
(* t_3 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos((0.5 * phi2)) * sin((phi1 * 0.5));
double t_3 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt(((t_3 * (t_1 * t_1)) + pow((t_2 - (t_0 * sin((0.5 * phi2)))), 2.0))), sqrt(((1.0 - pow(((t_0 * sin((phi2 * -0.5))) + t_2), 2.0)) + (t_3 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
t_0 = cos((phi1 * 0.5d0))
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))
t_3 = cos(phi1) * cos(phi2)
code = r * (2.0d0 * atan2(sqrt(((t_3 * (t_1 * t_1)) + ((t_2 - (t_0 * sin((0.5d0 * phi2)))) ** 2.0d0))), sqrt(((1.0d0 - (((t_0 * sin((phi2 * (-0.5d0)))) + t_2) ** 2.0d0)) + (t_3 * ((cos((lambda1 - lambda2)) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos((phi1 * 0.5));
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5));
double t_3 = Math.cos(phi1) * Math.cos(phi2);
return R * (2.0 * Math.atan2(Math.sqrt(((t_3 * (t_1 * t_1)) + Math.pow((t_2 - (t_0 * Math.sin((0.5 * phi2)))), 2.0))), Math.sqrt(((1.0 - Math.pow(((t_0 * Math.sin((phi2 * -0.5))) + t_2), 2.0)) + (t_3 * ((Math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos((phi1 * 0.5)) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5)) t_3 = math.cos(phi1) * math.cos(phi2) return R * (2.0 * math.atan2(math.sqrt(((t_3 * (t_1 * t_1)) + math.pow((t_2 - (t_0 * math.sin((0.5 * phi2)))), 2.0))), math.sqrt(((1.0 - math.pow(((t_0 * math.sin((phi2 * -0.5))) + t_2), 2.0)) + (t_3 * ((math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) t_3 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_3 * Float64(t_1 * t_1)) + (Float64(t_2 - Float64(t_0 * sin(Float64(0.5 * phi2)))) ^ 2.0))), sqrt(Float64(Float64(1.0 - (Float64(Float64(t_0 * sin(Float64(phi2 * -0.5))) + t_2) ^ 2.0)) + Float64(t_3 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos((phi1 * 0.5)); t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = cos((0.5 * phi2)) * sin((phi1 * 0.5)); t_3 = cos(phi1) * cos(phi2); tmp = R * (2.0 * atan2(sqrt(((t_3 * (t_1 * t_1)) + ((t_2 - (t_0 * sin((0.5 * phi2)))) ^ 2.0))), sqrt(((1.0 - (((t_0 * sin((phi2 * -0.5))) + t_2) ^ 2.0)) + (t_3 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$3 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[(t$95$2 - N[(t$95$0 * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(t$95$0 * N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$3 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right)\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 \cdot \left(t\_1 \cdot t\_1\right) + {\left(t\_2 - t\_0 \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}}}{\sqrt{\left(1 - {\left(t\_0 \cdot \sin \left(\phi_2 \cdot -0.5\right) + t\_2\right)}^{2}\right) + t\_3 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified62.9%
div-sub62.9%
sin-diff63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr63.8%
div-sub62.9%
sin-diff63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr77.8%
*-commutative77.8%
*-commutative77.8%
fmm-def77.8%
*-commutative77.8%
*-commutative77.8%
*-commutative77.8%
distribute-lft-neg-in77.8%
sin-neg77.8%
distribute-rgt-neg-in77.8%
metadata-eval77.8%
*-commutative77.8%
*-commutative77.8%
Simplified77.8%
sin-mult77.9%
cos-sum77.9%
cos-277.9%
div-sub77.9%
+-inverses77.9%
Applied egg-rr77.9%
cos-077.9%
metadata-eval77.9%
Simplified77.9%
fma-undefine77.9%
*-commutative77.9%
*-commutative77.9%
*-commutative77.9%
*-commutative77.9%
Applied egg-rr77.9%
Final simplification77.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (sin (* phi1 0.5)))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (cos (* phi1 0.5))))
(*
R
(*
2.0
(atan2
(sqrt
(+ (* t_2 (* t_0 t_0)) (pow (- t_1 (* t_3 (sin (* 0.5 phi2)))) 2.0)))
(sqrt
(+
(-
1.0
(pow (fma (cos (* 0.5 phi2)) t_1 (* t_3 (sin (* phi2 -0.5)))) 2.0))
(* t_2 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = sin((phi1 * 0.5));
double t_2 = cos(phi1) * cos(phi2);
double t_3 = cos((phi1 * 0.5));
return R * (2.0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + pow((t_1 - (t_3 * sin((0.5 * phi2)))), 2.0))), sqrt(((1.0 - pow(fma(cos((0.5 * phi2)), t_1, (t_3 * sin((phi2 * -0.5)))), 2.0)) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(phi1 * 0.5)) t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = cos(Float64(phi1 * 0.5)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_2 * Float64(t_0 * t_0)) + (Float64(t_1 - Float64(t_3 * sin(Float64(0.5 * phi2)))) ^ 2.0))), sqrt(Float64(Float64(1.0 - (fma(cos(Float64(0.5 * phi2)), t_1, Float64(t_3 * sin(Float64(phi2 * -0.5)))) ^ 2.0)) + Float64(t_2 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$2 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[(t$95$1 - N[(t$95$3 * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1 + N[(t$95$3 * N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$2 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := \cos \left(\phi_1 \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 \cdot \left(t\_0 \cdot t\_0\right) + {\left(t\_1 - t\_3 \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}}}{\sqrt{\left(1 - {\left(\mathsf{fma}\left(\cos \left(0.5 \cdot \phi_2\right), t\_1, t\_3 \cdot \sin \left(\phi_2 \cdot -0.5\right)\right)\right)}^{2}\right) + t\_2 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified62.9%
div-sub62.9%
sin-diff63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr63.8%
div-sub62.9%
sin-diff63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr77.8%
*-commutative77.8%
*-commutative77.8%
fmm-def77.8%
*-commutative77.8%
*-commutative77.8%
*-commutative77.8%
distribute-lft-neg-in77.8%
sin-neg77.8%
distribute-rgt-neg-in77.8%
metadata-eval77.8%
*-commutative77.8%
*-commutative77.8%
Simplified77.8%
sin-mult77.9%
cos-sum77.9%
cos-277.9%
div-sub77.9%
+-inverses77.9%
Applied egg-rr77.9%
cos-077.9%
metadata-eval77.9%
Simplified77.9%
Taylor expanded in phi2 around 0 64.5%
Final simplification64.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
t_1
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* 0.5 phi2))))
2.0)))
(sqrt (- (- 1.0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)) t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))), 2.0))), sqrt(((1.0 - pow(sin(((phi1 - phi2) / 2.0)), 2.0)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((0.5d0 * phi2)))) ** 2.0d0))), sqrt(((1.0d0 - (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(((Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((0.5 * phi2)))), 2.0))), Math.sqrt(((1.0 - Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(((math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((0.5 * phi2)))), 2.0))), math.sqrt(((1.0 - math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(0.5 * phi2)))) ^ 2.0))), sqrt(Float64(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))) ^ 2.0))), sqrt(((1.0 - (sin(((phi1 - phi2) / 2.0)) ^ 2.0)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}}}{\sqrt{\left(1 - {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified62.9%
div-sub62.9%
sin-diff63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr63.8%
Final simplification63.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))
(*
R
(*
2.0
(atan2
(sqrt
(+
t_0
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* 0.5 phi2))))
2.0)))
(sqrt (- 1.0 (+ t_0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0));
return R * (2.0 * atan2(sqrt((t_0 + pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))), 2.0))), sqrt((1.0 - (t_0 + pow(sin((0.5 * (phi1 - phi2))), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))
code = r * (2.0d0 * atan2(sqrt((t_0 + (((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((0.5d0 * phi2)))) ** 2.0d0))), sqrt((1.0d0 - (t_0 + (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((t_0 + Math.pow(((Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((0.5 * phi2)))), 2.0))), Math.sqrt((1.0 - (t_0 + Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) return R * (2.0 * math.atan2(math.sqrt((t_0 + math.pow(((math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((0.5 * phi2)))), 2.0))), math.sqrt((1.0 - (t_0 + math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + (Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(0.5 * phi2)))) ^ 2.0))), sqrt(Float64(1.0 - Float64(t_0 + (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)); tmp = R * (2.0 * atan2(sqrt((t_0 + (((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))) ^ 2.0))), sqrt((1.0 - (t_0 + (sin((0.5 * (phi1 - phi2))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}}}{\sqrt{1 - \left(t\_0 + {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified62.9%
div-sub62.9%
sin-diff63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr63.8%
Taylor expanded in phi1 around 0 63.8%
Final simplification63.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (or (<= phi1 -3.7e-6) (not (<= phi1 4e-5)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ phi1 2.0)) 2.0)
(*
(+ (cos (- phi1 phi2)) (cos (+ phi1 phi2)))
(/ (- 1.0 (cos (- lambda1 lambda2))) 4.0))))
(sqrt (- 1.0 (+ t_0 (* (cos phi1) t_2)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* (cos phi2) t_2)))
(sqrt (- 1.0 (+ t_0 (* t_1 (* (* (cos phi1) (cos phi2)) t_1)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi1 <= -3.7e-6) || !(phi1 <= 4e-5)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi1 / 2.0)), 2.0) + ((cos((phi1 - phi2)) + cos((phi1 + phi2))) * ((1.0 - cos((lambda1 - lambda2))) / 4.0)))), sqrt((1.0 - (t_0 + (cos(phi1) * t_2))))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_0 + (cos(phi2) * t_2))), sqrt((1.0 - (t_0 + (t_1 * ((cos(phi1) * cos(phi2)) * t_1)))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
if ((phi1 <= (-3.7d-6)) .or. (.not. (phi1 <= 4d-5))) then
tmp = r * (2.0d0 * atan2(sqrt(((sin((phi1 / 2.0d0)) ** 2.0d0) + ((cos((phi1 - phi2)) + cos((phi1 + phi2))) * ((1.0d0 - cos((lambda1 - lambda2))) / 4.0d0)))), sqrt((1.0d0 - (t_0 + (cos(phi1) * t_2))))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_0 + (cos(phi2) * t_2))), sqrt((1.0d0 - (t_0 + (t_1 * ((cos(phi1) * cos(phi2)) * t_1)))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi1 <= -3.7e-6) || !(phi1 <= 4e-5)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((phi1 / 2.0)), 2.0) + ((Math.cos((phi1 - phi2)) + Math.cos((phi1 + phi2))) * ((1.0 - Math.cos((lambda1 - lambda2))) / 4.0)))), Math.sqrt((1.0 - (t_0 + (Math.cos(phi1) * t_2))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_0 + (Math.cos(phi2) * t_2))), Math.sqrt((1.0 - (t_0 + (t_1 * ((Math.cos(phi1) * Math.cos(phi2)) * t_1)))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) tmp = 0 if (phi1 <= -3.7e-6) or not (phi1 <= 4e-5): tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((phi1 / 2.0)), 2.0) + ((math.cos((phi1 - phi2)) + math.cos((phi1 + phi2))) * ((1.0 - math.cos((lambda1 - lambda2))) / 4.0)))), math.sqrt((1.0 - (t_0 + (math.cos(phi1) * t_2)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_0 + (math.cos(phi2) * t_2))), math.sqrt((1.0 - (t_0 + (t_1 * ((math.cos(phi1) * math.cos(phi2)) * t_1))))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if ((phi1 <= -3.7e-6) || !(phi1 <= 4e-5)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi1 / 2.0)) ^ 2.0) + Float64(Float64(cos(Float64(phi1 - phi2)) + cos(Float64(phi1 + phi2))) * Float64(Float64(1.0 - cos(Float64(lambda1 - lambda2))) / 4.0)))), sqrt(Float64(1.0 - Float64(t_0 + Float64(cos(phi1) * t_2))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(cos(phi2) * t_2))), sqrt(Float64(1.0 - Float64(t_0 + Float64(t_1 * Float64(Float64(cos(phi1) * cos(phi2)) * t_1)))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; tmp = 0.0; if ((phi1 <= -3.7e-6) || ~((phi1 <= 4e-5))) tmp = R * (2.0 * atan2(sqrt(((sin((phi1 / 2.0)) ^ 2.0) + ((cos((phi1 - phi2)) + cos((phi1 + phi2))) * ((1.0 - cos((lambda1 - lambda2))) / 4.0)))), sqrt((1.0 - (t_0 + (cos(phi1) * t_2)))))); else tmp = R * (2.0 * atan2(sqrt((t_0 + (cos(phi2) * t_2))), sqrt((1.0 - (t_0 + (t_1 * ((cos(phi1) * cos(phi2)) * t_1))))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -3.7e-6], N[Not[LessEqual[phi1, 4e-5]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi1 + phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(1.0 - N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[(t$95$1 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -3.7 \cdot 10^{-6} \lor \neg \left(\phi_1 \leq 4 \cdot 10^{-5}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1}{2}\right)}^{2} + \left(\cos \left(\phi_1 - \phi_2\right) + \cos \left(\phi_1 + \phi_2\right)\right) \cdot \frac{1 - \cos \left(\lambda_1 - \lambda_2\right)}{4}}}{\sqrt{1 - \left(t\_0 + \cos \phi_1 \cdot t\_2\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + \cos \phi_2 \cdot t\_2}}{\sqrt{1 - \left(t\_0 + t\_1 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right)\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -3.7000000000000002e-6 or 4.00000000000000033e-5 < phi1 Initial program 47.8%
Taylor expanded in phi1 around inf 48.4%
Taylor expanded in phi2 around 0 49.0%
associate-*l*49.1%
cos-mult49.7%
sin-mult49.8%
frac-times49.8%
Applied egg-rr49.8%
associate-/l*49.8%
+-commutative49.8%
+-commutative49.8%
cos-049.8%
Simplified49.8%
if -3.7000000000000002e-6 < phi1 < 4.00000000000000033e-5Initial program 76.4%
Taylor expanded in phi1 around 0 76.4%
Final simplification63.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_2 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (or (<= phi1 -3.7e-6) (not (<= phi1 0.00125)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ phi1 2.0)) 2.0)
(*
(+ (cos (- phi1 phi2)) (cos (+ phi1 phi2)))
(/ (- 1.0 (cos (- lambda1 lambda2))) 4.0))))
(sqrt (- 1.0 (+ t_1 (* (cos phi1) t_2)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(sqrt
(- 1.0 (+ (* (cos phi2) t_2) (pow (sin (* phi2 -0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi1 <= -3.7e-6) || !(phi1 <= 0.00125)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi1 / 2.0)), 2.0) + ((cos((phi1 - phi2)) + cos((phi1 + phi2))) * ((1.0 - cos((lambda1 - lambda2))) / 4.0)))), sqrt((1.0 - (t_1 + (cos(phi1) * t_2))))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))), sqrt((1.0 - ((cos(phi2) * t_2) + pow(sin((phi2 * -0.5)), 2.0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_2 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
if ((phi1 <= (-3.7d-6)) .or. (.not. (phi1 <= 0.00125d0))) then
tmp = r * (2.0d0 * atan2(sqrt(((sin((phi1 / 2.0d0)) ** 2.0d0) + ((cos((phi1 - phi2)) + cos((phi1 + phi2))) * ((1.0d0 - cos((lambda1 - lambda2))) / 4.0d0)))), sqrt((1.0d0 - (t_1 + (cos(phi1) * t_2))))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))), sqrt((1.0d0 - ((cos(phi2) * t_2) + (sin((phi2 * (-0.5d0))) ** 2.0d0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi1 <= -3.7e-6) || !(phi1 <= 0.00125)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((phi1 / 2.0)), 2.0) + ((Math.cos((phi1 - phi2)) + Math.cos((phi1 + phi2))) * ((1.0 - Math.cos((lambda1 - lambda2))) / 4.0)))), Math.sqrt((1.0 - (t_1 + (Math.cos(phi1) * t_2))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + (t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)))), Math.sqrt((1.0 - ((Math.cos(phi2) * t_2) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_2 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) tmp = 0 if (phi1 <= -3.7e-6) or not (phi1 <= 0.00125): tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((phi1 / 2.0)), 2.0) + ((math.cos((phi1 - phi2)) + math.cos((phi1 + phi2))) * ((1.0 - math.cos((lambda1 - lambda2))) / 4.0)))), math.sqrt((1.0 - (t_1 + (math.cos(phi1) * t_2)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + (t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)))), math.sqrt((1.0 - ((math.cos(phi2) * t_2) + math.pow(math.sin((phi2 * -0.5)), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if ((phi1 <= -3.7e-6) || !(phi1 <= 0.00125)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi1 / 2.0)) ^ 2.0) + Float64(Float64(cos(Float64(phi1 - phi2)) + cos(Float64(phi1 + phi2))) * Float64(Float64(1.0 - cos(Float64(lambda1 - lambda2))) / 4.0)))), sqrt(Float64(1.0 - Float64(t_1 + Float64(cos(phi1) * t_2))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * t_2) + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; t_2 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; tmp = 0.0; if ((phi1 <= -3.7e-6) || ~((phi1 <= 0.00125))) tmp = R * (2.0 * atan2(sqrt(((sin((phi1 / 2.0)) ^ 2.0) + ((cos((phi1 - phi2)) + cos((phi1 + phi2))) * ((1.0 - cos((lambda1 - lambda2))) / 4.0)))), sqrt((1.0 - (t_1 + (cos(phi1) * t_2)))))); else tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))), sqrt((1.0 - ((cos(phi2) * t_2) + (sin((phi2 * -0.5)) ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -3.7e-6], N[Not[LessEqual[phi1, 0.00125]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi1 + phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(1.0 - N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 + N[(N[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_2 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -3.7 \cdot 10^{-6} \lor \neg \left(\phi_1 \leq 0.00125\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1}{2}\right)}^{2} + \left(\cos \left(\phi_1 - \phi_2\right) + \cos \left(\phi_1 + \phi_2\right)\right) \cdot \frac{1 - \cos \left(\lambda_1 - \lambda_2\right)}{4}}}{\sqrt{1 - \left(t\_1 + \cos \phi_1 \cdot t\_2\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)}}{\sqrt{1 - \left(\cos \phi_2 \cdot t\_2 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -3.7000000000000002e-6 or 0.00125000000000000003 < phi1 Initial program 47.8%
Taylor expanded in phi1 around inf 48.4%
Taylor expanded in phi2 around 0 49.0%
associate-*l*49.1%
cos-mult49.7%
sin-mult49.8%
frac-times49.8%
Applied egg-rr49.8%
associate-/l*49.8%
+-commutative49.8%
+-commutative49.8%
cos-049.8%
Simplified49.8%
if -3.7000000000000002e-6 < phi1 < 0.00125000000000000003Initial program 76.4%
Taylor expanded in phi1 around 0 76.4%
Final simplification63.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (* (cos phi1) (cos phi2))))
(if (or (<= phi2 -5.8e-6) (not (<= phi2 3.5e-7)))
(*
(atan2
(sqrt (+ (* (cos phi2) t_1) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt
(-
1.0
(fma
t_2
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))
(* R 2.0))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (* t_2 t_0))))
(sqrt
(- 1.0 (+ (* (cos phi1) t_1) (pow (sin (* phi1 0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = cos(phi1) * cos(phi2);
double tmp;
if ((phi2 <= -5.8e-6) || !(phi2 <= 3.5e-7)) {
tmp = atan2(sqrt(((cos(phi2) * t_1) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((1.0 - fma(t_2, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), pow(sin((0.5 * (phi1 - phi2))), 2.0))))) * (R * 2.0);
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_2 * t_0)))), sqrt((1.0 - ((cos(phi1) * t_1) + pow(sin((phi1 * 0.5)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_2 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((phi2 <= -5.8e-6) || !(phi2 <= 3.5e-7)) tmp = Float64(atan(sqrt(Float64(Float64(cos(phi2) * t_1) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_2, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))))) * Float64(R * 2.0)); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_2 * t_0)))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_1) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -5.8e-6], N[Not[LessEqual[phi2, 3.5e-7]], $MachinePrecision]], N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$2 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_2 \leq -5.8 \cdot 10^{-6} \lor \neg \left(\phi_2 \leq 3.5 \cdot 10^{-7}\right):\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_1 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(t\_2, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}} \cdot \left(R \cdot 2\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(t\_2 \cdot t\_0\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_1 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -5.8000000000000004e-6 or 3.49999999999999984e-7 < phi2 Initial program 50.6%
associate-*r*50.6%
*-commutative50.6%
Simplified50.6%
Applied egg-rr25.4%
*-lft-identity25.4%
*-commutative25.4%
*-commutative25.4%
cancel-sign-sub-inv25.4%
metadata-eval25.4%
Simplified25.4%
Taylor expanded in phi1 around 0 51.8%
if -5.8000000000000004e-6 < phi2 < 3.49999999999999984e-7Initial program 76.9%
Taylor expanded in phi2 around 0 76.9%
Final simplification63.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (* (cos phi1) (cos phi2))))
(if (or (<= phi2 -5.3e-9) (not (<= phi2 2.5e-26)))
(*
(atan2
(sqrt (+ (* (cos phi2) t_1) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt
(-
1.0
(fma
t_2
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))
(* R 2.0))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_0 (* t_2 t_0)) (pow (sin (/ phi1 2.0)) 2.0)))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) (* (cos phi1) t_1)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = cos(phi1) * cos(phi2);
double tmp;
if ((phi2 <= -5.3e-9) || !(phi2 <= 2.5e-26)) {
tmp = atan2(sqrt(((cos(phi2) * t_1) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((1.0 - fma(t_2, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), pow(sin((0.5 * (phi1 - phi2))), 2.0))))) * (R * 2.0);
} else {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_2 * t_0)) + pow(sin((phi1 / 2.0)), 2.0))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * t_1)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_2 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((phi2 <= -5.3e-9) || !(phi2 <= 2.5e-26)) tmp = Float64(atan(sqrt(Float64(Float64(cos(phi2) * t_1) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_2, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))))) * Float64(R * 2.0)); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_2 * t_0)) + (sin(Float64(phi1 / 2.0)) ^ 2.0))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * t_1)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -5.3e-9], N[Not[LessEqual[phi2, 2.5e-26]], $MachinePrecision]], N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(t$95$2 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_2 \leq -5.3 \cdot 10^{-9} \lor \neg \left(\phi_2 \leq 2.5 \cdot 10^{-26}\right):\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_1 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(t\_2, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}} \cdot \left(R \cdot 2\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_2 \cdot t\_0\right) + {\sin \left(\frac{\phi_1}{2}\right)}^{2}}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot t\_1}}\right)\\
\end{array}
\end{array}
if phi2 < -5.30000000000000031e-9 or 2.5000000000000001e-26 < phi2 Initial program 52.2%
associate-*r*52.2%
*-commutative52.2%
Simplified52.2%
Applied egg-rr27.3%
*-lft-identity27.3%
*-commutative27.3%
*-commutative27.3%
cancel-sign-sub-inv27.3%
metadata-eval27.3%
Simplified27.3%
Taylor expanded in phi1 around 0 53.0%
if -5.30000000000000031e-9 < phi2 < 2.5000000000000001e-26Initial program 76.0%
Taylor expanded in phi1 around inf 75.2%
div-sub76.0%
sin-diff76.0%
div-inv76.0%
metadata-eval76.0%
div-inv76.0%
metadata-eval76.0%
div-inv76.0%
metadata-eval76.0%
div-inv76.0%
metadata-eval76.0%
Applied egg-rr75.3%
Taylor expanded in phi2 around 0 75.2%
+-commutative75.2%
associate--r+75.3%
unpow275.3%
*-commutative75.3%
*-commutative75.3%
1-sub-sin75.3%
*-commutative75.3%
*-commutative75.3%
unpow275.3%
*-commutative75.3%
Simplified75.3%
Final simplification63.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_2 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_2 (* t_0 t_0)) t_1))
(sqrt
(+ (- 1.0 t_1) (* t_2 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0 - t_1) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_2 = cos(phi1) * cos(phi2)
code = r * (2.0d0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0d0 - t_1) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = Math.cos(phi1) * Math.cos(phi2);
return R * (2.0 * Math.atan2(Math.sqrt(((t_2 * (t_0 * t_0)) + t_1)), Math.sqrt(((1.0 - t_1) + (t_2 * ((Math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_2 = math.cos(phi1) * math.cos(phi2) return R * (2.0 * math.atan2(math.sqrt(((t_2 * (t_0 * t_0)) + t_1)), math.sqrt(((1.0 - t_1) + (t_2 * ((math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_2 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_2 * Float64(t_0 * t_0)) + t_1)), sqrt(Float64(Float64(1.0 - t_1) + Float64(t_2 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; t_2 = cos(phi1) * cos(phi2); tmp = R * (2.0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0 - t_1) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$2 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] + N[(t$95$2 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 \cdot \left(t\_0 \cdot t\_0\right) + t\_1}}{\sqrt{\left(1 - t\_1\right) + t\_2 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified62.9%
sin-mult77.9%
cos-sum77.9%
cos-277.9%
div-sub77.9%
+-inverses77.9%
Applied egg-rr63.0%
cos-077.9%
metadata-eval77.9%
Simplified63.0%
Final simplification63.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt
(+
t_1
(*
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))))))
(sqrt (- 1.0 (+ t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
return R * (2.0 * atan2(sqrt((t_1 + (cos(phi1) * (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2)))))))), sqrt((1.0 - (t_1 + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt((t_1 + (cos(phi1) * (cos(phi2) * (0.5d0 + ((-0.5d0) * cos((lambda1 - lambda2)))))))), sqrt((1.0d0 - (t_1 + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + (Math.cos(phi1) * (Math.cos(phi2) * (0.5 + (-0.5 * Math.cos((lambda1 - lambda2)))))))), Math.sqrt((1.0 - (t_1 + (t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) return R * (2.0 * math.atan2(math.sqrt((t_1 + (math.cos(phi1) * (math.cos(phi2) * (0.5 + (-0.5 * math.cos((lambda1 - lambda2)))))))), math.sqrt((1.0 - (t_1 + (t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(cos(phi1) * Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))))))), sqrt(Float64(1.0 - Float64(t_1 + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; tmp = R * (2.0 * atan2(sqrt((t_1 + (cos(phi1) * (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2)))))))), sqrt((1.0 - (t_1 + (t_0 * ((cos(phi1) * cos(phi2)) * t_0))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)\right)}}{\sqrt{1 - \left(t\_1 + t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\right)}}\right)
\end{array}
\end{array}
Initial program 62.9%
pow162.9%
Applied egg-rr61.4%
unpow161.4%
associate-*l*61.4%
cancel-sign-sub-inv61.4%
metadata-eval61.4%
Simplified61.4%
Final simplification61.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (* (cos phi1) (cos phi2))))
(if (or (<= phi2 -1.5e-9) (not (<= phi2 2.5e-26)))
(*
(atan2
(sqrt (+ (* (cos phi2) t_1) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt
(-
1.0
(fma
t_2
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))
(* R 2.0))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_0 (* t_2 t_0)) (pow (sin (/ phi1 2.0)) 2.0)))
(sqrt
(+
1.0
(- (- (/ (cos (- phi1 phi2)) 2.0) 0.5) (* (cos phi1) t_1))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = cos(phi1) * cos(phi2);
double tmp;
if ((phi2 <= -1.5e-9) || !(phi2 <= 2.5e-26)) {
tmp = atan2(sqrt(((cos(phi2) * t_1) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((1.0 - fma(t_2, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), pow(sin((0.5 * (phi1 - phi2))), 2.0))))) * (R * 2.0);
} else {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_2 * t_0)) + pow(sin((phi1 / 2.0)), 2.0))), sqrt((1.0 + (((cos((phi1 - phi2)) / 2.0) - 0.5) - (cos(phi1) * t_1))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_2 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((phi2 <= -1.5e-9) || !(phi2 <= 2.5e-26)) tmp = Float64(atan(sqrt(Float64(Float64(cos(phi2) * t_1) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_2, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))))) * Float64(R * 2.0)); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_2 * t_0)) + (sin(Float64(phi1 / 2.0)) ^ 2.0))), sqrt(Float64(1.0 + Float64(Float64(Float64(cos(Float64(phi1 - phi2)) / 2.0) - 0.5) - Float64(cos(phi1) * t_1))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -1.5e-9], N[Not[LessEqual[phi2, 2.5e-26]], $MachinePrecision]], N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(t$95$2 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_2 \leq -1.5 \cdot 10^{-9} \lor \neg \left(\phi_2 \leq 2.5 \cdot 10^{-26}\right):\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_1 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(t\_2, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}} \cdot \left(R \cdot 2\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_2 \cdot t\_0\right) + {\sin \left(\frac{\phi_1}{2}\right)}^{2}}}{\sqrt{1 + \left(\left(\frac{\cos \left(\phi_1 - \phi_2\right)}{2} - 0.5\right) - \cos \phi_1 \cdot t\_1\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -1.49999999999999999e-9 or 2.5000000000000001e-26 < phi2 Initial program 52.2%
associate-*r*52.2%
*-commutative52.2%
Simplified52.2%
Applied egg-rr27.3%
*-lft-identity27.3%
*-commutative27.3%
*-commutative27.3%
cancel-sign-sub-inv27.3%
metadata-eval27.3%
Simplified27.3%
Taylor expanded in phi1 around 0 53.0%
if -1.49999999999999999e-9 < phi2 < 2.5000000000000001e-26Initial program 76.0%
Taylor expanded in phi1 around inf 75.2%
Taylor expanded in phi2 around 0 75.2%
unpow275.2%
sin-mult75.3%
div-inv75.3%
metadata-eval75.3%
div-inv75.3%
metadata-eval75.3%
div-inv75.3%
metadata-eval75.3%
div-inv75.3%
metadata-eval75.3%
Applied egg-rr75.3%
div-sub75.3%
+-inverses75.3%
cos-075.3%
metadata-eval75.3%
distribute-lft-out75.3%
metadata-eval75.3%
*-rgt-identity75.3%
Simplified75.3%
Final simplification63.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (- lambda1 lambda2)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (* 0.5 (- lambda1 lambda2)))))
(if (or (<= phi1 -6.6e-7) (not (<= phi1 4.4e-5)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ phi1 2.0)) 2.0)
(* (+ (cos (- phi1 phi2)) (cos (+ phi1 phi2))) (/ (- 1.0 t_0) 4.0))))
(sqrt
(-
1.0
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (cos phi1) (pow t_2 2.0))))))))
(*
(* R 2.0)
(atan2
(hypot (sin (* 0.5 (- phi1 phi2))) (* t_2 (sqrt t_1)))
(sqrt
(-
1.0
(fma t_1 (+ 0.5 (* -0.5 t_0)) (pow (sin (* phi2 -0.5)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((lambda1 - lambda2));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin((0.5 * (lambda1 - lambda2)));
double tmp;
if ((phi1 <= -6.6e-7) || !(phi1 <= 4.4e-5)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi1 / 2.0)), 2.0) + ((cos((phi1 - phi2)) + cos((phi1 + phi2))) * ((1.0 - t_0) / 4.0)))), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (cos(phi1) * pow(t_2, 2.0)))))));
} else {
tmp = (R * 2.0) * atan2(hypot(sin((0.5 * (phi1 - phi2))), (t_2 * sqrt(t_1))), sqrt((1.0 - fma(t_1, (0.5 + (-0.5 * t_0)), pow(sin((phi2 * -0.5)), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(lambda1 - lambda2)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) tmp = 0.0 if ((phi1 <= -6.6e-7) || !(phi1 <= 4.4e-5)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi1 / 2.0)) ^ 2.0) + Float64(Float64(cos(Float64(phi1 - phi2)) + cos(Float64(phi1 + phi2))) * Float64(Float64(1.0 - t_0) / 4.0)))), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(cos(phi1) * (t_2 ^ 2.0)))))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), Float64(t_2 * sqrt(t_1))), sqrt(Float64(1.0 - fma(t_1, Float64(0.5 + Float64(-0.5 * t_0)), (sin(Float64(phi2 * -0.5)) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -6.6e-7], N[Not[LessEqual[phi1, 4.4e-5]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi1 + phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(1.0 - t$95$0), $MachinePrecision] / 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[Power[t$95$2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$2 * N[Sqrt[t$95$1], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * N[(0.5 + N[(-0.5 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\lambda_1 - \lambda_2\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
\mathbf{if}\;\phi_1 \leq -6.6 \cdot 10^{-7} \lor \neg \left(\phi_1 \leq 4.4 \cdot 10^{-5}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1}{2}\right)}^{2} + \left(\cos \left(\phi_1 - \phi_2\right) + \cos \left(\phi_1 + \phi_2\right)\right) \cdot \frac{1 - t\_0}{4}}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \cos \phi_1 \cdot {t\_2}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), t\_2 \cdot \sqrt{t\_1}\right)}{\sqrt{1 - \mathsf{fma}\left(t\_1, 0.5 + -0.5 \cdot t\_0, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\\
\end{array}
\end{array}
if phi1 < -6.6000000000000003e-7 or 4.3999999999999999e-5 < phi1 Initial program 47.8%
Taylor expanded in phi1 around inf 48.4%
Taylor expanded in phi2 around 0 49.0%
associate-*l*49.1%
cos-mult49.7%
sin-mult49.8%
frac-times49.8%
Applied egg-rr49.8%
associate-/l*49.8%
+-commutative49.8%
+-commutative49.8%
cos-049.8%
Simplified49.8%
if -6.6000000000000003e-7 < phi1 < 4.3999999999999999e-5Initial program 76.4%
associate-*r*76.4%
*-commutative76.4%
Simplified76.4%
Applied egg-rr55.7%
*-lft-identity55.7%
*-commutative55.7%
*-commutative55.7%
cancel-sign-sub-inv55.7%
metadata-eval55.7%
Simplified55.7%
Taylor expanded in phi1 around 0 55.7%
*-commutative55.7%
Simplified55.7%
Final simplification52.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (* (cos phi1) t_0)))
(if (or (<= phi1 -3.2e-6) (not (<= phi1 0.00038)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ phi1 2.0)) 2.0)
(*
(+ (cos (- phi1 phi2)) (cos (+ phi1 phi2)))
(/ (- 1.0 (cos (- lambda1 lambda2))) 4.0))))
(sqrt (- 1.0 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))))))
(*
R
(*
2.0
(atan2
(expm1 (log1p (hypot (sin (* 0.5 (- phi1 phi2))) (sqrt t_1))))
(sqrt (- 1.0 (* (cos phi2) t_0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = cos(phi1) * t_0;
double tmp;
if ((phi1 <= -3.2e-6) || !(phi1 <= 0.00038)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi1 / 2.0)), 2.0) + ((cos((phi1 - phi2)) + cos((phi1 + phi2))) * ((1.0 - cos((lambda1 - lambda2))) / 4.0)))), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)))));
} else {
tmp = R * (2.0 * atan2(expm1(log1p(hypot(sin((0.5 * (phi1 - phi2))), sqrt(t_1)))), sqrt((1.0 - (cos(phi2) * t_0)))));
}
return tmp;
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = Math.cos(phi1) * t_0;
double tmp;
if ((phi1 <= -3.2e-6) || !(phi1 <= 0.00038)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((phi1 / 2.0)), 2.0) + ((Math.cos((phi1 - phi2)) + Math.cos((phi1 + phi2))) * ((1.0 - Math.cos((lambda1 - lambda2))) / 4.0)))), Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.expm1(Math.log1p(Math.hypot(Math.sin((0.5 * (phi1 - phi2))), Math.sqrt(t_1)))), Math.sqrt((1.0 - (Math.cos(phi2) * t_0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_1 = math.cos(phi1) * t_0 tmp = 0 if (phi1 <= -3.2e-6) or not (phi1 <= 0.00038): tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((phi1 / 2.0)), 2.0) + ((math.cos((phi1 - phi2)) + math.cos((phi1 + phi2))) * ((1.0 - math.cos((lambda1 - lambda2))) / 4.0)))), math.sqrt((1.0 - (math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1))))) else: tmp = R * (2.0 * math.atan2(math.expm1(math.log1p(math.hypot(math.sin((0.5 * (phi1 - phi2))), math.sqrt(t_1)))), math.sqrt((1.0 - (math.cos(phi2) * t_0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = Float64(cos(phi1) * t_0) tmp = 0.0 if ((phi1 <= -3.2e-6) || !(phi1 <= 0.00038)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi1 / 2.0)) ^ 2.0) + Float64(Float64(cos(Float64(phi1 - phi2)) + cos(Float64(phi1 + phi2))) * Float64(Float64(1.0 - cos(Float64(lambda1 - lambda2))) / 4.0)))), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)))))); else tmp = Float64(R * Float64(2.0 * atan(expm1(log1p(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), sqrt(t_1)))), sqrt(Float64(1.0 - Float64(cos(phi2) * t_0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]}, If[Or[LessEqual[phi1, -3.2e-6], N[Not[LessEqual[phi1, 0.00038]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi1 + phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(1.0 - N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(Exp[N[Log[1 + N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2 + N[Sqrt[t$95$1], $MachinePrecision] ^ 2], $MachinePrecision]], $MachinePrecision]] - 1), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \cos \phi_1 \cdot t\_0\\
\mathbf{if}\;\phi_1 \leq -3.2 \cdot 10^{-6} \lor \neg \left(\phi_1 \leq 0.00038\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1}{2}\right)}^{2} + \left(\cos \left(\phi_1 - \phi_2\right) + \cos \left(\phi_1 + \phi_2\right)\right) \cdot \frac{1 - \cos \left(\lambda_1 - \lambda_2\right)}{4}}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\mathsf{expm1}\left(\mathsf{log1p}\left(\mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), \sqrt{t\_1}\right)\right)\right)}{\sqrt{1 - \cos \phi_2 \cdot t\_0}}\right)\\
\end{array}
\end{array}
if phi1 < -3.1999999999999999e-6 or 3.8000000000000002e-4 < phi1 Initial program 47.8%
Taylor expanded in phi1 around inf 48.4%
Taylor expanded in phi2 around 0 49.0%
associate-*l*49.1%
cos-mult49.7%
sin-mult49.8%
frac-times49.8%
Applied egg-rr49.8%
associate-/l*49.8%
+-commutative49.8%
+-commutative49.8%
cos-049.8%
Simplified49.8%
if -3.1999999999999999e-6 < phi1 < 3.8000000000000002e-4Initial program 76.4%
Taylor expanded in phi1 around inf 45.9%
Taylor expanded in phi1 around 0 45.9%
Taylor expanded in phi2 around 0 46.7%
expm1-log1p-u46.7%
unpow246.7%
add-sqr-sqrt46.7%
hypot-define46.8%
div-inv46.8%
metadata-eval46.8%
Applied egg-rr46.8%
Final simplification48.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (* (cos phi1) t_0)))
(if (or (<= phi1 -2.1e-7) (not (<= phi1 6.5e-6)))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ phi1 2.0)) 2.0) t_1))
(sqrt (- 1.0 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))))))
(*
R
(*
2.0
(atan2
(expm1 (log1p (hypot (sin (* 0.5 (- phi1 phi2))) (sqrt t_1))))
(sqrt (- 1.0 (* (cos phi2) t_0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = cos(phi1) * t_0;
double tmp;
if ((phi1 <= -2.1e-7) || !(phi1 <= 6.5e-6)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi1 / 2.0)), 2.0) + t_1)), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)))));
} else {
tmp = R * (2.0 * atan2(expm1(log1p(hypot(sin((0.5 * (phi1 - phi2))), sqrt(t_1)))), sqrt((1.0 - (cos(phi2) * t_0)))));
}
return tmp;
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = Math.cos(phi1) * t_0;
double tmp;
if ((phi1 <= -2.1e-7) || !(phi1 <= 6.5e-6)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((phi1 / 2.0)), 2.0) + t_1)), Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.expm1(Math.log1p(Math.hypot(Math.sin((0.5 * (phi1 - phi2))), Math.sqrt(t_1)))), Math.sqrt((1.0 - (Math.cos(phi2) * t_0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_1 = math.cos(phi1) * t_0 tmp = 0 if (phi1 <= -2.1e-7) or not (phi1 <= 6.5e-6): tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((phi1 / 2.0)), 2.0) + t_1)), math.sqrt((1.0 - (math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1))))) else: tmp = R * (2.0 * math.atan2(math.expm1(math.log1p(math.hypot(math.sin((0.5 * (phi1 - phi2))), math.sqrt(t_1)))), math.sqrt((1.0 - (math.cos(phi2) * t_0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = Float64(cos(phi1) * t_0) tmp = 0.0 if ((phi1 <= -2.1e-7) || !(phi1 <= 6.5e-6)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi1 / 2.0)) ^ 2.0) + t_1)), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)))))); else tmp = Float64(R * Float64(2.0 * atan(expm1(log1p(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), sqrt(t_1)))), sqrt(Float64(1.0 - Float64(cos(phi2) * t_0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]}, If[Or[LessEqual[phi1, -2.1e-7], N[Not[LessEqual[phi1, 6.5e-6]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(Exp[N[Log[1 + N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2 + N[Sqrt[t$95$1], $MachinePrecision] ^ 2], $MachinePrecision]], $MachinePrecision]] - 1), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \cos \phi_1 \cdot t\_0\\
\mathbf{if}\;\phi_1 \leq -2.1 \cdot 10^{-7} \lor \neg \left(\phi_1 \leq 6.5 \cdot 10^{-6}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1}{2}\right)}^{2} + t\_1}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\mathsf{expm1}\left(\mathsf{log1p}\left(\mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), \sqrt{t\_1}\right)\right)\right)}{\sqrt{1 - \cos \phi_2 \cdot t\_0}}\right)\\
\end{array}
\end{array}
if phi1 < -2.1e-7 or 6.4999999999999996e-6 < phi1 Initial program 47.8%
Taylor expanded in phi1 around inf 48.4%
Taylor expanded in phi2 around 0 49.0%
Taylor expanded in phi2 around 0 49.6%
if -2.1e-7 < phi1 < 6.4999999999999996e-6Initial program 76.4%
Taylor expanded in phi1 around inf 45.9%
Taylor expanded in phi1 around 0 45.9%
Taylor expanded in phi2 around 0 46.7%
expm1-log1p-u46.7%
unpow246.7%
add-sqr-sqrt46.7%
hypot-define46.8%
div-inv46.8%
metadata-eval46.8%
Applied egg-rr46.8%
Final simplification48.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* (cos phi1) t_0)))
(sqrt (- 1.0 (* (cos phi2) t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (cos(phi1) * t_0))), sqrt((1.0 - (cos(phi2) * t_0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (cos(phi1) * t_0))), sqrt((1.0d0 - (cos(phi2) * t_0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (Math.cos(phi1) * t_0))), Math.sqrt((1.0 - (Math.cos(phi2) * t_0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (math.cos(phi1) * t_0))), math.sqrt((1.0 - (math.cos(phi2) * t_0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(cos(phi1) * t_0))), sqrt(Float64(1.0 - Float64(cos(phi2) * t_0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (cos(phi1) * t_0))), sqrt((1.0 - (cos(phi2) * t_0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \cos \phi_1 \cdot t\_0}}{\sqrt{1 - \cos \phi_2 \cdot t\_0}}\right)
\end{array}
\end{array}
Initial program 62.9%
Taylor expanded in phi1 around inf 46.8%
Taylor expanded in phi1 around 0 33.9%
Taylor expanded in phi2 around 0 34.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2)))))
(*
R
(*
2.0
(atan2
(hypot (sin (* phi2 -0.5)) t_0)
(sqrt (- 1.0 (* (cos phi2) (pow t_0 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
return R * (2.0 * atan2(hypot(sin((phi2 * -0.5)), t_0), sqrt((1.0 - (cos(phi2) * pow(t_0, 2.0))))));
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((0.5 * (lambda1 - lambda2)));
return R * (2.0 * Math.atan2(Math.hypot(Math.sin((phi2 * -0.5)), t_0), Math.sqrt((1.0 - (Math.cos(phi2) * Math.pow(t_0, 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (lambda1 - lambda2))) return R * (2.0 * math.atan2(math.hypot(math.sin((phi2 * -0.5)), t_0), math.sqrt((1.0 - (math.cos(phi2) * math.pow(t_0, 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) return Float64(R * Float64(2.0 * atan(hypot(sin(Float64(phi2 * -0.5)), t_0), sqrt(Float64(1.0 - Float64(cos(phi2) * (t_0 ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (lambda1 - lambda2))); tmp = R * (2.0 * atan2(hypot(sin((phi2 * -0.5)), t_0), sqrt((1.0 - (cos(phi2) * (t_0 ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] ^ 2 + t$95$0 ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_2 \cdot -0.5\right), t\_0\right)}{\sqrt{1 - \cos \phi_2 \cdot {t\_0}^{2}}}\right)
\end{array}
\end{array}
Initial program 62.9%
Taylor expanded in phi1 around inf 46.8%
Taylor expanded in phi1 around 0 33.9%
Taylor expanded in phi2 around 0 34.6%
Taylor expanded in phi1 around 0 32.5%
unpow232.5%
unpow232.5%
hypot-define32.9%
*-commutative32.9%
Simplified32.9%
herbie shell --seed 2024188
(FPCore (R lambda1 lambda2 phi1 phi2)
:name "Distance on a great circle"
:precision binary64
(* R (* 2.0 (atan2 (sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* (* (* (cos phi1) (cos phi2)) (sin (/ (- lambda1 lambda2) 2.0))) (sin (/ (- lambda1 lambda2) 2.0))))) (sqrt (- 1.0 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* (* (* (cos phi1) (cos phi2)) (sin (/ (- lambda1 lambda2) 2.0))) (sin (/ (- lambda1 lambda2) 2.0))))))))))